We are seeing a significant rise in customers’ email accounts being used to distribute spam, having had their account credentials compromised.

In many cases this has been purely down to simple, fairly obvious, passwords being used. Would you believe that we have 276 mailboxes that use ‘password’ as their password? Or 73 with the password 123456?

It’s important for all our customers that we minimise the potential of our mail servers becoming blacklisted, so where patterns of outbound sending indicate a compromised mailbox and the distribution of spam, we will block the account from sending out any further email until the password is changed and a virus scan on the end users equipment performed if required.

This helps mitigate against blacklisting, but isn’t perfect by any means as it’s reactive in nature.

Whilst we can’t improve on the way we identify compromised mailboxes, we can improve the tools we give Partners to re-enable outbound SMTP immediately following a block.

Currently we send out an alert when an account is locked and rely on you contacting us to re-enable. Add to that, any blocking we’ve done has been at account level, rather than individual mailboxes, so one compromised mailbox can lead to outbound emails being blocked for the whole account.

As of Tuesday 27th June we are implementing a new process for dealing with compromised accounts:

Blocks can now be applied at individual mailbox level, rather than account level. This means that only the affected mailbox will be restricted from sending, rather than all users on that account.

Our systems will now automatically unlock any affected mailboxes once the user, or administrator, has changed the password.

Next Tuesday all mailboxes with passwords we deem to be easily compromised (for example, using part of the email address) will be blocked from sending outbound email until their password has been changed. This will only affect a relatively small proportion of our overall customer base, but needs to be implemented as the issue of compromised email boxes is on the rise.

We very much hope you’ll welcome the changes we’ve made which, as well as giving more control to customers in the event their email credentials are compromised, it also encourages everyone to think a little more seriously about the security of their email!

In the ongoing war against the spammers, we have put a lot of effort over the last year or two in looking at the effectiveness of various methods, and thought it might be helpful to give a bit of a behind-the-scenes look at some of the lists and methodologies we use and their relative effectiveness. What these stats don’t show is the amount of false positives or the amount of spams that we miss as with our diverse user base it is impossible to measure these things accurately.

We try to be quite aggressive at detecting spams as the majority of our users make use of what we call auto-whitelisting, where anyone they send an email to automatically gets added to their whitelist and doesn’t get checked for spam in the future (well not at stage 2 anyway – see below).

The first stage of our spam blocking is the most aggressive, and most sensitive. If we have false positives here, we tend to find out about it because we reject the connections based on the IP address that is trying to connect to us.

I’ve included links below so you can investigate and find out more about any particular list.

Firstly, let’s look at connections to our servers. Taking a sample day, of Wednesday December 14th 2016, we received a total of 6,680,134 inbound SMTP connections. Here’s what we did with them.

Of those 1,040,196 accepted connections, we received 1,008,901 individual emails. These were then broken up as follows:

Whitelisted

138,055

Blacklisted

3,513

Too Large to Scan

6,960

Not scanned (user not enabled anti-spam)

131,480

Scanned

728,893

So we now have a grand total of 728,893 emails to feed into our anti-spam servers. These run a piece of software called Spamassassin that looks for patterns in emails that mean they are probably spam and score them accordingly. Unfortunately, the spammers have access to this, and the good ones are very clever at making their spams not look like spam to a computer (though still obviously spam to a human), so we rely quite heavily on various blacklists to identify spam for us.

In the last couple of years, the spammers have become even more sophisticated and found ways to send out millions of spams before the blacklists are able to list them. The blacklists are fighting back, however, with new lists such as InstantRBL and faster listings (particularly good at URIBL).

Taking our sample day with 728,893 spams to be scanned, here is how many are caught by each different method/list employed. These stats show unique hits (so, for example, if something is caught by two lists, or one list and other Spamassassin rules, it won’t show up).

It’s hard to draw a pretty chart from all of this. However, here are the headline figures. 6,680,134 inbound connections, 891,949 emails delivered to inboxes, which represents 13% of the total. 131,480 of those didn’t get a chance to be scanned because our end user didn’t have the feature enabled.

So there you have it, it’s an ongoing battle, and the battleground keeps shifting. The spammers have access to all of the same tools that we do – that’s the nature of the internet, so they will keep trying to find new ways to beat the system, and we will keep trying to find new ways to stop them.